Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method for aggregating an energy service from a number of participants for use by a power-system operator, comprising: estimating, by a computer, a probe price to elicit energy service from one or more participants; providing the probe price to a respective participant in a group of participants; receiving, from the respective participant, a supply-function approximation that includes a slope, α, and an intercept, β, to map a price of the energy service to a supply amount that the respective participant can provide; calculating, by the computer, a purchase price, λ, for the group of participants of the energy service using the function: λ = C - ∑ i = 1 N cons α i ∑ i = 1 N cons β i , wherein C indicates a total supply quantity, and i iterates over N participants in the group of participants; responsive to the purchase price not being approximately equal to the probe price: sending, to a respective participant, an updated probe price that includes the purchase price; receiving an updated supply function approximation from the respective participant; and recalculating the purchase price using the updated supply function approximation; and responsive to the purchase price being approximately equal to the probe price, providing the purchase price to the participants.
A computer-implemented method aggregates energy services from multiple participants for a power-system operator. It starts by estimating a "probe price" to see how much energy each participant is willing to supply. This price is sent to each participant. Each participant responds with a "supply-function approximation" (a simple formula with slope α and intercept β) that estimates their energy supply at different prices. The system then calculates a "purchase price" (λ) using the formula λ = (C - Σαi) / Σβi, where C is the total desired energy supply, and the summation is over all participants. If this purchase price isn't close enough to the initial probe price, the system updates the probe price with the calculated purchase price, gets new supply approximations, and recalculates the purchase price. This continues until the purchase price converges with the probe price. Finally, the agreed-upon purchase price is sent to all participants.
2. The method of claim 1 , further comprising providing a bid to the power-system operator to provide the desired amount of energy service at a contracted time in the future.
Building on the energy service aggregation method, the system further includes the step of submitting a bid to the power-system operator, offering to provide a specific amount of energy service at a future, contracted time. The goal is to meet the operator's energy demands at that time. The system is acting as an aggregator representing the combined energy services of the multiple participants.
3. The method of claim 2 , wherein the operations of providing the probe price, receiving the supply-function approximations, and generating the purchase price occur after the bid and before the contracted time.
In the energy service aggregation method where a bid is provided to a power-system operator for a contracted time, the process of sending probe prices to participants, receiving their supply function approximations, and calculating the purchase price happens after the initial bid is made but before the energy is actually needed at the contracted time. This allows the aggregator to refine the supply commitments based on real-time conditions closer to the delivery time.
4. The method of claim 1 , wherein determining whether the purchase price approximately equals the probe price includes determining whether the purchase price meets restrictions included in the supply-function approximation.
In the energy service aggregation method, when determining if the calculated purchase price is close enough to the probe price, the system also checks if the purchase price meets certain restrictions included in the participant's supply-function approximation. These restrictions could be limits on how much energy they can realistically provide or minimum price requirements. The iterative adjustment stops only when both the price converges and the restrictions are satisfied.
5. The method of claim 1 , wherein the purchase price is a minimum price in a range of prices.
In the energy service aggregation method, the calculated purchase price is selected to be the minimum acceptable price within a range of possible prices. This ensures that the aggregator secures the energy service at the lowest possible cost while still meeting the total supply requirements of the power-system operator.
6. The method of claim 1 , wherein the energy service includes at least one of: a demand response in which the participants agree to reduce energy demand, a commitment by the participants to provide power, and a commitment by the participants to provide ancillary power services.
In the energy service aggregation method, the "energy service" being aggregated can include one or more of the following: participants reducing their energy demand (demand response), participants committing to actively supply power to the grid, and/or participants committing to provide ancillary power services like frequency regulation or voltage support.
7. The method of claim 1 , wherein aggregating the energy service facilitates regulation of a power system by the power-system operator.
The energy service aggregation method facilitates the power-system operator's ability to regulate the power system. By aggregating the energy resources of multiple participants, the operator gains a more flexible and responsive control over the grid's supply and demand, leading to better stability and reliability.
8. The method of claim 7 , wherein the regulation occurs over a time interval that is less than 15 seconds.
In the energy service aggregation method where it facilitates power system regulation, the regulation occurs over a very short time interval of less than 15 seconds. This rapid response time is crucial for maintaining grid stability during sudden fluctuations in supply or demand.
9. The method of claim 1 , wherein aggregating the energy service facilitates load following in a power system by the power-system operator.
The energy service aggregation method facilitates load following in the power system, allowing the power-system operator to match the system's electricity generation to the constantly changing electricity demand, maintaining system stability.
10. The method of claim 9 , wherein the load following occurs over a time interval that is less than one minute.
In the energy service aggregation method where it facilitates load following, the load following action occurs over a time interval of less than one minute. This enables the system to quickly adapt to fluctuations in demand, ensuring that the supply always matches the load.
11. The method of claim 1 , wherein generating the purchase price involves performing Newton's method based at least in part on the supply-function approximation.
In the energy service aggregation method, the calculation of the purchase price involves using Newton's method, a numerical technique, which relies on the participant's supply-function approximation to find the price that balances supply and demand.
12. The method of claim 1 , wherein, after generation of the purchase price, the purchase price is fixed for the participant, who is obliged to provide a corresponding portion of the desired amount of the energy service.
In the energy service aggregation method, once the purchase price is determined for a participant, that price is fixed. The participant is then obligated to provide the corresponding portion of the total energy service requested, effectively creating a binding agreement at the calculated price.
13. The method of claim 1 , wherein the supply-function approximation includes a restriction on a binding responsibility of the participant.
In the energy service aggregation method, the supply-function approximation provided by a participant includes a restriction on their binding responsibility. This could be a limit on the total amount of energy they are willing to commit or specific conditions under which they can reduce their commitment.
14. The method of claim 1 , wherein the supply-function approximation includes a tangent to the supply function at the probe price.
In the energy service aggregation method, the supply-function approximation provided by the participant includes a tangent line to their actual supply function at the current probe price. This linear approximation simplifies the calculation of the purchase price while still reflecting the participant's responsiveness to price changes around the operating point.
15. The method of claim 1 , wherein the supply-function approximation is a vector that includes a series of supply-function approximations and associated prices that facilitate calculation of purchase prices in a sequence of time intervals.
In the energy service aggregation method, the supply-function approximation is a vector or array containing a series of supply-function approximations paired with their corresponding prices. This allows the system to calculate purchase prices across a sequence of time intervals, enabling dynamic and time-varying optimization of energy service aggregation.
16. The method of claim 15 , wherein a dynamical model is used to compute future effects of demand responses on the participant over time.
In the energy service aggregation method using a series of supply function approximations, a dynamical model is used to predict how demand responses from participants will affect them over time. This model takes into account the time-dependent nature of energy consumption and helps optimize the overall system performance.
17. The method of claim 15 , where the supply function approximations are used in a model predictive control implementation.
In the energy service aggregation method using a series of supply function approximations, those approximations are utilized within a Model Predictive Control (MPC) implementation. This allows the system to anticipate future conditions and proactively adjust energy service aggregation to optimize performance over a defined time horizon.
18. The method of claim 1 , wherein the supply-function approximation includes at least one of: a difference equation, a differential equation and a finite state machine.
In the energy service aggregation method, the supply-function approximation provided by a participant can take various forms, including a difference equation, a differential equation, or a finite state machine, allowing for more complex and accurate representation of their supply characteristics.
19. The method of claim 1 , wherein the supply-function approximation is selected from a set of predetermined functions.
In the energy service aggregation method, the supply-function approximation is selected from a pre-defined set of possible functions. This simplifies the process for participants and ensures that the system can easily process and utilize the provided information.
20. The method of claim 1 , further comprising coupling the energy service with other power sources or other power loads.
The energy service aggregation method can be combined with other power sources (like renewable energy) or other power loads (like industrial facilities) to optimize overall grid management and improve energy efficiency.
21. The method of claim 1 , wherein generating the purchase price further involves minimizing a cost or disutility function of the participant.
In the energy service aggregation method, the process of calculating the purchase price also involves minimizing a cost or "disutility" function for the participant. This means the system considers the participant's individual costs and preferences when determining the price, leading to a more equitable and sustainable energy service arrangement.
22. A computer-program product for use in conjunction with a computer system, the computer-program product comprising a non-transitory computer-readable storage medium and a computer-program mechanism embedded therein to aggregate an energy service from a number of participants for use by a power-system operator, the computer-program mechanism including: instructions for estimating a probe price to elicit energy service from one or more participants; instructions for providing the probe price to a respective participant in a group of participants; instructions for receiving, from the respective participant, a supply-function approximation that includes a slope, α, and an intercept, β, to map a price of the energy service to a supply amount that the respective participant can provide; instructions for calculating a purchase price, λ, the group of participants of the energy service using the function: λ = C - ∑ i = 1 N cons α i ∑ i = 1 N cons β i , wherein C indicates a total supply quantity, and i iterates over N participants in the group of participants; instructions for recalculating the purchase price responsive to the purchase price not being approximately equal to the probe price, wherein recalculating the purchase price involves: sending, to a respective participant, an updated probe price that includes the purchase price; receiving an updated supply function approximation from the respective participant; and recalculating the purchase price using the updated supply function approximation; and instructions for providing the purchase price to the participants responsive to the purchase price being approximately equal to the probe price.
A computer program stored on a non-transitory medium aggregates energy services from participants for a power-system operator. The program estimates a probe price, sends it to participants, and receives supply-function approximations (with slope α and intercept β). It calculates a purchase price (λ) using the formula λ = (C - Σαi) / Σβi, where C is total supply. If the purchase price isn't close to the probe price, the program updates the probe price, gets new supply approximations, and recalculates the purchase price iteratively. Once the prices converge, the program provides the purchase price to the participants. The program performs the same steps as the energy aggregation method.
23. A computer system, comprising: a processor; memory; and a program module, wherein the program module is stored in the memory and configured to be executed by the processor, the program module to aggregate an energy service from a number of participants for use by a power-system operator, the program module including: instructions for estimating a probe price to elicit energy service from one or more participants; instructions for providing the probe price to a respective participant in a group of participants; instructions for receiving, from the respective participant, a supply-function approximation that includes a slope, α, and an intercept, β, to map a price of the energy service to a supply amount that the respective participant can provide; instructions for calculating a purchase price, λ, for the group of participants of the energy service using the function: λ = C - ∑ i = 1 N cons α i ∑ i = 1 N cons β i , wherein C indicates a total supply quantity, and i iterates over N participants in the group of participants; instructions for recalculating the purchase price responsive to the purchase price not being approximately equal to the probe price, wherein recalculating the purchase price involves: sending, to a respective participant, an updated probe price that includes the purchase price; receiving an updated supply function approximation from the respective participant; and recalculating the purchase price using the updated supply function approximation; and instructions for providing the purchase price to the participants responsive to the purchase price being approximately equal to the probe price.
A computer system aggregates energy services from participants for a power-system operator. It includes a processor, memory, and a program module. The program estimates a probe price, sends it to participants, and receives supply-function approximations (with slope α and intercept β). It calculates a purchase price (λ) using the formula λ = (C - Σαi) / Σβi, where C is total supply. If the purchase price isn't close to the probe price, the program updates the probe price, gets new supply approximations, and recalculates the purchase price iteratively. Once the prices converge, the program provides the purchase price to the participants. The system performs the same steps as the energy aggregation method.
Unknown
August 26, 2014
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